System and method for evaluating changes in the efficiency of an HVAC system

ABSTRACT

The invention comprises systems and methods for evaluating changes in the operational efficiency of an HVAC system over time. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system, and status of said HVAC system. One or more processors receives measurements of outside temperatures from at least one source other than said HVAC system and compares said temperature measurements from said first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet, or any correction thereto,are hereby incorporated by reference into this application under 37 CFR1.57.

BACKGROUND OF THE INVENTION Field of the Invention

This invention relates to the use of thermostatic HVAC controls that areconnected to a computer network. More specifically, communicatingthermostats are combined with a computer network in order to evaluatechanges in the operational efficiency of an HVAC system over time.

Background

Climate control systems such as heating and cooling systems forbuildings (heating, ventilation and cooling, or HVAC systems) have beencontrolled for decades by thermostats. At the most basic level, athermostat includes a means to allow a user to set a desiredtemperature, a means to sense actual temperature, and a means to signalthe heating and/or cooling devices to turn on or off in order to try tochange the actual temperature to equal the desired temperature. The mostbasic versions of thermostats use components such as a coiledbi-metallic spring to measure actual temperature and a mercury switchthat opens or completes a circuit when the spring coils or uncoils withtemperature changes. More recently, electronic digital thermostats havebecome prevalent. These thermostats use solid-state devices such asthermistors or thermal diodes to measure temperature, andmicroprocessor-based circuitry to control the switch and to store andoperate based upon user-determined protocols for temperature vs. time.

These programmable thermostats generally offer a very restrictive userinterface, limited by the cost of the devices, the limited real estateof the small wall-mounted boxes, and the inability to take into accountmore than two variables: the desired temperature set by the user, andthe ambient temperature sensed by the thermostat. Users can generallyonly set one series of commands per day, and in order to change oneparameter (e.g., to change the late-night temperature) the user oftenhas to cycle through several other parameters by repeatedly pressing oneor two buttons.

Because the interface of programmable thermostats is so poor, thesignificant theoretical savings that are possible with them (sometimescited as 25% of heating and cooling costs) are rarely realized. Inpractice, studies have fund that more than 50% of users never programtheir thermostats at all. Significant percentages of the thermostatsthat are programmed are programmed sub-optimally, in part because, onceprogrammed, people tend to not to re-invest the time needed to changethe settings very often.

A second problem with standard programmable thermostats is that theyrepresent only a small evolutionary step beyond the first, purelymechanical thermostats. Like the first thermostats, they only have twoinput signals—ambient temperature and the preset desired temperature.The entire advance with programmable thermostats is that they can shiftbetween multiple present temperatures at different times.

SUMMARY OF THE INVENTION

There are many other sources of information that could be used toincrease comfort, decrease energy use, or both. For example, outsidetemperature and humidity strongly affect subjective comfort. On a 95degree, 90 percent humidity day in August, when people tend to dress inlightweight clothing, a house cooled to 70 degrees will feel cool oreven uncomfortably cold. On a below-freezing day in January, when peopletend to wear sweaters and heavier clothes, that same 70 degree home willfeel too warm. It would therefore be advantageous for a thermostatsystem to automatically incorporate information about external weatherconditions when setting the desired temperature.

Thermostats are used to regulate temperature for the benefit of theoccupants in a given space. (Usually this means people, but it can ofcourse also mean critical equipment, such as in a room filled withcomputer equipment.) In general, thermostats read temperature from thesensor located within the “four corners” of the thermostat. With aproperly designed system, the thermostat may well be located such thatthe temperature read at the precise location of the thermostataccurately reflects the conditions where the human (or other) occupantstend to be. But there are many reasons and circumstances in which thatwill not be the case. A single thermostat may produce accurate readingsin some circumstances but not others; it may be located in a place farfrom the occupants, or too far from the ductwork controlled by thethermostat, etc. In one house, for example, the thermostat may belocated in a spot that receives direct sunlight on hot afternoons. Thiscould cause the thermostat to sense that the local ambient temperatureis extremely high, and as a result signal the A/C to run too long,making the rest of the home too cold, and wasting considerable energy.In another house, the thermostat may be located in a hallway withoutductwork or where the nearby ducts have been closed. In such a scenario,the thermostat is likely to (correctly) report cold temperatures in thewinter, leading the heating system to overheat the rest of the house andwaste considerable energy.

These problems can be reduced or eliminated through use of additionalremote temperature sensors connected to the thermostat's controlcircuitry. However, such systems require additional hardware, additionalthermostat complexity, and skilled installation and configuration.

It would therefore be desirable for a thermostat system using only asingle temperature sensor to take such sub-optimal installations intoaccount and to correct for the erroneous readings generated by suchthermostats.

Different structures will respond to changes in conditions such asexternal temperature in different ways. For example, houses built 50 ormore years ago will generally have little or no insulation, be poorlysealed, and have simple single-glazed windows. Such houses will do avery poor job of retaining internal heat in the winter and rejectingexternal heat in the summer. In the absence of applications of thermalmeasures such as heating and air conditioning, the inside temperature insuch houses will trend to track outside temperatures very closely. Suchhouses may be said to have low thermal mass. A house built in recentyears, using contemporary techniques for energy efficiency such as highlevels of insulation, double-glazed windows and other techniques, will,in the absence of intervention, tend to absorb external heat and releaseinternal heat very slowly. The newer house can be thought of as havinghigher thermal mass than the older house.

A conventional thermostat has no mechanism by which it might take thethermal mass of the structure into account, but thermal masssignificantly affects many parameters relating to energy efficiency.

The cost to an electric utility to produce power varies over time.Indeed, the cost of production between low demand and peak demandperiods can vary by as much as an order of magnitude. Traditionally,residential customers paid the same price regardless of time or the costto produce. Thus consumers have had little financial incentive to reduceconsumption during periods of high demand and high production cost. Manyelectric utilities are now seeking to bring various forms of variablerates to the retail energy markets. Under such schemes, consumers canreduce costs by taking into account not just how much energy they use,but when they use it.

Thus many consumers now can see real benefits from optimizing not justthe total number of kilowatt-hours of electricity consumed, but alsooptimizing when it is used. The optimum strategy for energy use overtime will vary based upon many variables, one of which is the thermalmass of the structure being heated or cooled. In a structure with highthermal mass, heating and cooling can effectively be shifted away fromhigh cost periods to lower cost “shoulder” periods with little or noeffect on comfort. If, for example, a utility charges much higher rateson hot summer afternoons, it is likely that pre-cooling a high-thermalmass structure just before the high-cost period and then shutting downthe air conditioning during the peak will allow the house to remaincomfortable. But in a house with low thermal mass, the benefits ofpre-cooling will quickly dissipate, and the house will rapidly becomeuncomfortable if the air conditioning is shut off. Thus it would beadvantageous for a temperature control system to take thermal mass intoaccount when setting desired temperatures.

Many factors affect the efficiency of HVAC systems. Some may be thoughtof as essentially fixed, such as the theoretical efficiency of a centralair conditioner (often expressed as its SEER rating), the matching of agiven system to the characteristics of a given home, the location andsize of forced-air ductwork, etc. Other contributors to efficiency aremore dynamic, such as clogged filters, refrigerant leaks, duct leakageand “pop-offs,” and the like.

Most of these problems are likely to manifest themselves in the form ofhigher energy bills. But the “signature” of each different problem canbe discerned from the way in which each such problem affects the cycletimes of a given HVAC system over time and relative to weatherconditions and the performance of other HVAC systems in other houses. Iftwo otherwise identical houses are located next door to each other andhave gas furnaces, but one is rated at 50,000 BTUs and the other israted at 100,000 BTUs, the cycle times for the higher-capacity furnaceshould be shorter than for the lower-capacity unit. If both of thosesame houses have identical furnaces, but one has a clogged filter, thecycle times should be longer in the house with the clogged filter.Because cycling of the HVAC system is controlled by the thermostat,those differences in cycle time would be reflected in the data sensed byand control signals generated by the thermostat. It would beadvantageous for a thermostat system to be able to use that informationto diagnose problems and make recommendations based upon that data.

These needs are satisfied by at least one embodiment of the inventionthat includes a system for calculating a value for the effective thermalmass of a building comprising: at least one HVAC control system thatmeasures temperature at at least a first location conditioned by saidHVAC system, and reporting said temperature measurements as well as thestatus of said HVAC control system; one or more processors that receivemeasurements of outside temperatures from at least one source other thansaid HVAC control systems and compare said temperature measurements fromsaid first location with expected temperature measurements wherein theexpected temperature measurements are based at least in part upon pasttemperature measurements obtained by said HVAC control system and saidoutside temperature measurements; and one or more databases that storeat least said temperatures measured at said first location over time;calculating one or more rates of change in temperature at said firstlocation; and relating said calculated rates of change to said outsidetemperature measurements.

Another embodiment includes a system for calculating a value for theoperational efficiency of an HVAC system comprising at least one HVACcontrol system that measures temperature at at least a first locationconditioned by said HVAC system, and reporting said temperaturemeasurements as well as the status of said HVAC control system; one ormore processors that receive measurements of outside temperatures fromat least one source other than said HVAC control systems and comparesaid temperature measurements from said first location with expectedtemperature measurements wherein the expected temperature measurementsare based at least in part upon past temperature measurements obtainedby said HVAC control system and said outside temperature measurements;and one or more databases that store at least said temperatures measuredat said first location over time; calculating one or more rates ofchange in temperature at said first location for periods during whichthe status of the HVAC system is “on”; calculating one or more rates ofchange in temperature at said first location for periods during whichthe status of the HVAC system is “off”; and relating said calculatedrates of change to said outside temperature measurements.

A further embodiment includes a system for evaluating changes in theoperational efficiency of an HVAC system over time comprising at leastone HVAC control system that measures temperature at at least a firstlocation conditioned by said HVAC system, and reporting said temperaturemeasurements as well as the status of said HVAC control system; one ormore processors that receive measurements of outside temperatures fromat least one source other than said HVAC control systems and comparesaid temperature measurements from said first location with expectedtemperature measurements wherein the expected temperature measurementsare based at least in part upon past temperature measurements obtainedby said HVAC control system and said outside temperature measurements;and one or more databases that store at least said temperatures measuredat said first location over time.

A further embodiment includes a system for detecting and correcting foranomalous behavior in HVAC control systems comprising a first HVACcontrol system that measures temperature at at least a first locationconditioned by said first HVAC system, and reporting said temperaturemeasurements as well as the status of said first HVAC control system; atleast a second HVAC control system that measures temperature at at leasta second location conditioned by said second HVAC system, and reportingsaid temperature measurements as well as the status of said second HVACcontrol system; one or more processors that receive measurements ofoutside temperatures from at least one source other than said first andsecond HVAC control systems and compare said temperature measurementsfrom said first HVAC controls system and said second HVAC control systemand said outside temperature measurements; and one or more databasesthat store said temperatures measurements.

In at least one embodiment, the invention comprises a thermostatattached to an HVAC system, a local network connecting the thermostat toa larger network such as the Internet, and one or more additionalthermostats attached to the network, and a server in bi-directionalcommunication with a plurality of such thermostats. The server logs theambient temperature sensed by each thermostat vs. time and the signalssent by the thermostats to their HVAC systems. The server preferablyalso logs outside temperature and humidity data for the geographiclocations for the buildings served by the connected HVAC systems. Suchinformation is widely available from various sources that publishdetailed weather information based on geographic areas such as by ZIPcode. The server also stores other data affecting the load upon thesystem, such as specific model of HVAC system, occupancy, buildingcharacteristics, etc. Some of this data may be supplied by theindividual users of the system, while other data may come fromthird-party sources such as the electric and other utilities who supplyenergy to those users.

Combining these data sources will also allow the server to calculate theeffective thermal mass of the structures conditioned by thosethermostats. By combining data from multiple thermostats in a givenneighborhood, the system can correct for flaws in the location of agiven thermostat, and can evaluate the efficiency of a given system, aswell as assist in the diagnosis of problems and malfunctions in suchsystems.

This and other advantages of certain embodiments of the invention areexplained in the detailed description and claims that make reference tothe accompanying diagrams and flowcharts.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example of an overall environment in which an embodimentof the invention may be used.

FIG. 2 shows a high-level illustration of the architecture of a networkshowing the relationship between the major elements of one embodiment ofthe subject invention.

FIG. 3 shows an embodiment of the website to be used as part of thesubject invention.

FIG. 4 shows a high-level schematic of the thermostat used as part ofthe subject invention.

FIG. 5 shows one embodiment of the database structure used as part ofthe subject invention

FIGS. 6a and 6b show graphical representations of inside and outsidetemperatures in two different homes, one with high thermal mass and onewith low thermal mass.

FIGS. 7a and 7b show graphical representations of inside and outsidetemperatures in the same homes as in FIGS. 6a and 6b , showing thecycling of the air conditioning systems in those houses.

FIGS. 8a and 8b show graphical representations of inside and outsidetemperatures in the same home as in FIGS. 6a and 7a , showing thecycling of the air conditioning on two different days in order todemonstrate the effect of a change in operating efficiency on theparameters measured by the thermostat.

FIGS. 9a and 9b show the effects of employing a pre-cooling strategy intwo different houses.

FIGS. 10a and 10b show graphical representations of inside and outsidetemperatures in two different homes in order to demonstrate how thesystem can correct for erroneous readings in one house by referencingreadings in another.

FIG. 11 is a flowchart illustrating the steps involved in calculatingthe effective thermal mass of a home using the subject invention.

FIG. 12 is a flowchart illustrating the steps involved in determiningwhether an HVAC system has developed a problem that impairs efficiencyusing the subject invention.

FIG. 13 is a flowchart illustrating the steps involved in correcting forerroneous readings in one house by referencing readings in another usingthe subject invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 shows an example of an overall environment 100 in which anembodiment of the invention may be used. The environment 100 includes aninteractive communication network 102 with computers 104 connectedthereto. Also connected to network 102 are one or more server computers106, which store information and make the information available tocomputers 104. The network 102 allows communication between and amongthe computers 104 and 106.

Presently preferred network 102 comprises a collection of interconnectedpublic and/or private networks that are linked to together by a set ofstandard protocols to form a distributed network. While network 102 isintended to refer to what is now commonly referred to as the Internet,it is also intended to encompass variations which may be made in thefuture, including changes additions to existing standard protocols.

When a user of the subject invention wishes to access information onnetwork 102, the buyer initiates connection from his computer 104. Forexample, the user invokes a browser, which executes on computer 104. Thebrowser, in turn, establishes a communication link with network 102.Once connected to network 102, the user can direct the browser to accessinformation on server 106.

One popular part of the Internet is the World Wide Web. The World WideWeb contains a large number of computers 104 and servers 106, whichstore HyperText Markup Language (HTML) documents capable of displayinggraphical and textual information. HTML is a standard coding conventionand set of codes for attaching presentation and linking attributes toinformational content within documents.

The servers 106 that provide offerings on the World Wide Web aretypically called websites. A website is often defined by an Internetaddress that has an associated electronic page. Generally, an electronicpage is a document that organizes the presentation of text graphicalimages, audio and video.

In addition to the Internet, the network 102 can comprise a wide varietyof interactive communication media. For example, network 102 can includelocal area networks, interactive television networks, telephonenetworks, wireless data systems, two-way cable systems, and the like.

In one embodiment, computers 104 and servers 106 are conventionalcomputers that are equipped with communications hardware such as modemor a network interface card. The computers include processors such asthose sold by Intel and AMD. Other processors may also be used,including general-purpose processors, multi-chip processors, embeddedprocessors and the like.

Computers 104 can also be handheld and wireless devices such as personaldigital assistants (PDAs), cellular telephones and other devices capableof accessing the network.

Computers 104 utilize a browser configured to interact with the WorldWide Web. Such browsers may include Microsoft Explorer, Mozilla,Firefox, Opera or Safari. They may also include browsers used onhandheld and wireless devices.

The storage medium may comprise any method of storing information. Itmay comprise random access memory (RAM), electronically erasableprogrammable read only memory (EEPROM), read only memory (ROM), harddisk, floppy disk, CD-ROM, optical memory, or other method of storingdata.

Computers 104 and 106 may use an operating system such as MicrosoftWindows, Apple Mac OS, Linux, Unix or the like.

Computers 106 may include a range of devices that provide information,sound, graphics and text, and may use a variety of operating systems andsoftware optimized for distribution of content via networks.

FIG. 2 illustrates in further detail the architecture of the specificcomponents connected to network 102 showing the relationship between themajor elements of one embodiment of the subject invention. Attached tothe network are thermostats 108 and computers 104 of various users.Connected to thermostats 108 are HVAC units 110. The HVAC units may beconventional air conditioners, heat pumps, or other devices fortransferring heat into or out of a building. Each user is connected tothe server 106 via wired or wireless connection such as Ethernet or awireless protocol such as IEEE 802.11, a gateway 110 that connects thecomputer and thermostat to the Internet via a broadband connection suchas a digital subscriber line (DSL) or other form of broadband connectionto the World Wide Web. Server 106 contains the content to be served asweb pages and viewed by computers 104, as well as databases containinginformation used by the servers.

In the currently preferred embodiment, the website 200 includes a numberof components accessible to the user, as shown in FIG. 3. Thosecomponents may include a means to enter temperature settings 202, ameans to enter information about the user's home 204, a means to enterthe user's electricity bills 206, means to calculate energy savings thatcould result from various thermostat-setting strategies 208, and meansto enable and choose between various arrangements 210 for demandreduction with their electric utility provider as intermediated by thedemand reduction service provider.

FIG. 4 shows a high-level block diagram of thermostat 108 used as partof the subject invention. Thermostat 108 includes temperature sensingmeans 252, which may be a thermistor, thermal diode or other meanscommonly used in the design of electronic thermostats. It includes amicroprocessor 254, memory 256, a display 258, a power source 260, arelay 262, which turns the HVAC system on and off in response to asignal from the microprocessor, and contacts by which the relay isconnected to the wires that lead to the HVAC system. To allow thethermostat to communicate bi-directionally with the computer network,the thermostat also includes means 264 to connect the thermostat to alocal computer or to a wireless network. Such means could be in the formof Ethernet, wireless protocols such as IEEE 802.11, IEEE 802.15.4,Bluetooth, cellular systems such as CDMA, GSM and GPRS, or otherwireless protocols. The thermostat 250 may also include controls 266allowing users to change settings directly at the thermostat, but suchcontrols are not necessary to allow the thermostat to function.

The data used to generate the content delivered in the form of thewebsite is stored on one or more servers 106 within one or moredatabases. As shown in FIG. 5, the overall database structure 300 mayinclude temperature database 400, thermostat settings database 500,energy bill database 600, HVAC hardware database 700, weather database800, user database 900, transaction database 1000, product and servicedatabase 1100 and such other databases as may be needed to support theseand additional features.

The website will allow users of connected thermostats 250 to createpersonal accounts. Each user's account will store information indatabase 900, which tracks various attributes relative to users of thesite. Such attributes may include the make and model of the specificHVAC equipment in the user's home; the age and square footage of thehome, the solar orientation of the home, the location of the thermostatin the home, the user's preferred temperature settings, whether the useris a participant in a demand reduction program, etc.

As shown in FIG. 3, the website 200 will permit thermostat users toperform through the web browser substantially all of the programmingfunctions traditionally performed directly at the physical thermostat,such as temperature set points, the time at which the thermostat shouldbe at each set point, etc. Preferably the website will also allow usersto accomplish more advanced tasks such as allow users to program invacation settings for times when the HVAC system may be turned off orrun at more economical settings, and set macros that will allow changingthe settings of the temperature for all periods with a single gesturesuch as a mouse click.

In addition to using the system to allow better signaling and control ofthe HVAC system, which relies primarily on communication running fromthe server to the thermostat, the bi-directional communication will alsoallow the thermostat 108 to regularly measure and send to the serverinformation about the temperature in the building. By comparing outsidetemperature, inside temperature, thermostat settings, cycling behaviorof the HVAC system, and other variables, the system will be capable ofnumerous diagnostic and controlling functions beyond those of a standardthermostat.

For example, FIG. 6a shows a graph of inside temperature and outsidetemperature for a 24-hour period in House A, assuming no HVAC activity.House A has double-glazed windows and is well-insulated. When outsidetemperature 302 increases, inside temperature 304 follows, but withsignificant delay because of the thermal mass of the building.

FIG. 6b shows a graph of inside temperature and outside temperature forthe same 24-hour period in House B. House B is identical to House Aexcept that it (i) is located a block away and (ii) has single-glazedwindows and is poorly insulated. Because the two houses are so close toeach other, outside temperature 302 is the same in FIG. 6a and FIG. 6b .But the lower thermal mass of House B means that the rate at which theinside temperature 306 changes in response to the changes in outsidetemperature is much greater.

The differences in thermal mass will affect the cycling behavior of theHVAC systems in the two houses as well. FIG. 7a shows a graph of insidetemperature and outside temperature in House A for the same 24-hourperiod as shown in FIG. 6a , but assuming that the air conditioning isbeing used to try to maintain an internal temperature of 70 degrees.Outside temperatures 302 are the same as in FIGS. 6a and 6b . Because ofthe high thermal mass of the house, the air conditioning does not needto run for very long to maintain the target temperature, as shown byshaded areas 310.

FIG. 7b shows a graph of inside temperature 312 and outside temperature302 for the same 24-hour period in House B, assuming use of the airconditioning as in FIG. 7a . Because of the lower thermal mass of HouseB, the air conditioning system in House B has to run longer in order tomaintain the same target temperature, as shown by shaded areas 314.

Because server 106 a logs the temperature readings from inside eachhouse (whether once per minute or over some other interval), as well asthe timing and duration of air conditioning cycles, database 300 willcontain a history of the thermal performance of each house. Thatperformance data will allow the server 106 a to calculate an effectivethermal mass for each such structure—that is, the speed with thetemperature inside a given building will change in response to changesin outside temperature and differences between inside and outsidetemperatures. Because the server will also log these inputs againstother inputs including time of day, humidity, etc. the server will beable to predict, at any given time on any given day, the rate at whichinside temperature should change for given inside and outsidetemperatures.

The server will also record the responses of each house to changes inoutside conditions and cycling behavior over time. That will allow theserver to diagnose problems as and when they develop. For example, FIG.8a shows a graph of outside temperature 402, inside temperature 404 andHVAC cycle times 406 in House A for a specific 24-hour period on date X.Assume that, based upon comparison of the performance of House A on dateX relative to House A's historical performance, and in comparison to theperformance of House A relative to other nearby houses on date X, theHVAC system in House A is presumed to be operating at normal efficiency,and that House A is in the 86th percentile as compared to those otherhouses. FIG. 8b shows a graph of outside temperature 408, insidetemperature 410 and HVAC cycle times 412 in House A for the 24-hourperiod on date X+1. House A's HVAC system now requires significantlylonger cycle times in order to try to maintain the same internaltemperature. If those longer cycle times were due to higher outsidetemperatures, those cycle times would not indicate the existence of anyproblems. But because server 106 is aware of the outside temperature,the system can eliminate that possibility as an explanation for thehigher cycle times. Because server 106 is aware of the cycle times innearby houses, it can determine that, for example, on date X+1 theefficiency of House A is only in the 23^(rd) percentile. The server willbe programmed with a series of heuristics, gathered from predictivemodels and past experience, correlating the drop in efficiency and thetime interval over which it has occurred with different possible causes.For example, a 50% drop in efficiency in one day may be correlated witha refrigerant leak, especially if followed by a further drop inefficiency on the following day. A reduction of 10% over three monthsmay be correlated with a clogged filter. Based upon the historical datarecorded by the server, the server 106 will be able to alert thehomeowner that there is a problem and suggest a possible cause.

Because the system will be able to calculate effective thermal mass, itwill be able to determine the cost effectiveness of strategies such aspre-cooling for specific houses under different conditions. FIG. 9ashows a graph of outside temperature 502, inside temperature 504 andHVAC cycling times 506 in House A for a specific 24-hour period on dateY assuming that the system has used a pre-cooling strategy to avoidrunning the air conditioning during the afternoon, when rates arehighest. Because House A has high thermal mass, the house is capable of“banking” cool, and energy consumed during off-peak hours is in effectstored, allowing the house to remain cool even when the system is turnedoff. Temperatures keep rising during the period the air conditioning isoff, but because thermal mass is high, the rate of increase is low, andthe house is still comfortable six hours later. Although the pre-coolingcycle time is relatively long, the homeowner may still benefit becausethe price per kilowatt during the morning pre-cooling phase is lowerthan the price during the peak load period. FIG. 9b shows a graph of thesame outside temperature 502 in House B as in House A in FIG. 9a for thesame 24-hour period and using the same pre-cooling strategy as shown bycycling times 506. But because House B has minimal thermal mass, usingadditional electricity in order to pre-cool the house does not have thedesired effect; inside temperature 508 warms up so fast that the coolthat had been banked is quickly lost. Thus the system will recommendthat House A pre-cool in order to save money, but not recommendpre-cooling for House B.

The system can also help compensate for anomalies such as measurementinaccuracies due to factors such as poor thermostat location. It iswell-known that thermostats should be placed in a location that will belikely to experience “average” temperatures for the overall structure,and should be isolated from windows and other influences that could biasthe temperatures they “see.” But for various reasons, not all thermostatinstallations fir that ideal. FIG. 10a shows a graph of outsidetemperature 602, the average inside temperature for the entire house604, and inside temperature as read by the thermostat 606 in House C fora specific 24-hour period on September 15^(th), assuming that thethermostat is located so that from 4 PM until 5:30 PM on that day thethermostat is in direct sunlight. Until the point at which the sun hitsthe thermostat, the average inside temperature and temperature as readby the thermostat track very closely. But when the direct sunlight hitsthe thermostat, the thermostat and the surrounding area can heat up,causing the internal temperature as read by the thermostat to divergesignificantly from the average temperature for the rest of the house.Conventional thermostats have no way of distinguishing this circumstancefrom a genuinely hot day, and will both over-cool the rest of the houseand waste considerable energy when it cycles the air conditioner inorder to reduce the temperature as sensed by the thermostat. If the airconditioning is turned off, this phenomenon will manifest as a spike intemperature as measured by the thermostat. If the air conditioning isturned on (and has sufficient capacity to respond to the distortedtemperature signal caused by the sunlight), this phenomenon will likelymanifest as relatively small changes in the temperature as sensed by thethermostat, but significantly increased HVAC usage (as well asexcessively lowered temperatures in the rest of the house, but thisresult may not be directly measured in a single sensor environment. Thesubject system, in contrast, has multiple mechanisms that will allow itto correct for such distortions. First, because the subject systemcompares the internal readings from House C with the externaltemperature, it will be obvious that the rise in temperature at 4:00 PMis not correlated with a corresponding change in outside temperature.Second, because the system is also monitoring the readings from thethermostat in nearby House D, which (as shown in FIG. 10b ) is exposedto the same outside temperature 602, but has no sudden rise in measuredinternal temperature 608 at 4:00, the system has further validation thatthe temperature increase is not caused by climatic conditions. Andfinally, because the system has monitored and recorded the temperaturereadings from the thermostat in House C for each previous day, and hascompared the changing times of the aberration with the progression ofthe sun, the system can distinguish the patterns likely to indicatesolar overheating from other potential causes.

FIG. 11 illustrates the steps involved in calculating comparativethermal mass, or the thermal mass index. In step 1102, the serverretrieves climate data related to home X. Such data may include currentoutside temperature, outside temperature during the preceding hours,outside humidity, wind direction and speed, whether the sun is obscuredby clouds, and other factors. In step 1104, the server retrieves HVACduty cycle data for home X. Such data may include target settings set bythe thermostat in current and previous periods, the timing of switch-onand switch-off events and other data. In step 1106, the server retrievesdata regarding recent temperature readings as recorded by the thermostatin home X. In step 1108, the server retrieves profile data for home X.Such data may include square footage and number of floors, when thehouse was built and/or renovated, the extent to which it is insulated,its address, make, model and age of its furnace and air conditioninghardware, and other data. In step 1110, the server retrieves the currentinside temperature reading as transmitted by the thermostat. In step1112, the server calculates the thermal mass index for the home underthose conditions; that is, for example, it calculates the likely rate ofchange for internal temperature in home X from a starting point of 70degrees when the outside temperature is 85 degrees at 3:00 PM on August10^(th) when the wind is blowing at 5 mph from the north and the sky iscloudy. The server accomplishes this by applying a basic algorithm thatweighs each of these external variables as well as variables for variouscharacteristics of the home itself (such as size, level of insulation,method of construction, etc.) and data from other houses andenvironments.

FIG. 12 illustrates the steps involved in diagnosing defects in the HVACsystem for specific home X. In step 1202, the server retrieves climatedata related to home X. Such data may include current outsidetemperature, outside temperature during the preceding hours, outsidehumidity, wind direction and speed, whether the sun is obscured byclouds, and other factors. In step 1204, the server retrieves HVAC dutycycle data for home X. Such data may include target settings set by thethermostat in current and previous periods, the timing of switch-on andswitch-off events and other data. In step 1206, the server retrievesdata regarding current and recent temperature readings as recorded bythe thermostat in home X. In step 1208, the server retrieves profiledata for home X. Such data may include square footage and number offloors, when the house was built and/or renovated, the extent to whichit is insulated, its address, make, model and age of its furnace and airconditioning hardware, and other data. In step 1210, the serverretrieves comparative data from other houses that have thermostats thatalso report to the server. Such data may include interior temperaturereadings, outside temperature for those specific locations, duty cycledata for the HVAC systems at those locations, profile data for thestructures and HVAC systems in those houses and the calculated thermalmass index for those other houses. In step 1212, the server calculatesthe current relative efficiency of home X as compared to other homes.Those comparisons will take into account differences in size, location,age, etc in making those comparisons.

The server will also take into account that relative efficiency is notabsolute, but will vary depending on conditions. For example, a housethat has extensive south-facing windows is likely to experiencesignificant solar gain. On sunny winter days, that home will appear moreefficient than on cloudy winter days. That same house will appear moreefficient at times of day and year when trees or overhangs shade thosewindows than it will when summer sun reaches those windows. Thus theserver will calculate efficiency under varying conditions.

In step 1214 the server compares the HVAC system's efficiency, correctedfor the relevant conditions, to its efficiency in the past. If thecurrent efficiency is substantially the same as the historicalefficiency, the server concludes 1216 that there is no defect and thediagnostic routine ends. If the efficiency has changed, the serverproceeds to compare the historical and current data against patterns ofchanges known to indicate specific problems. For example, in step 1218,the server compares that pattern of efficiency changes against the knownpattern for a clogged air filter, which is likely to show a slow,gradual degradation over a period of weeks or even months. If thepattern of degradation matches the clogged filter paradigm, the servercreates and transmits to the homeowner a message 1220 alerting thehomeowner to the possible problem. If the problem does not match theclogged filter paradigm, the system compares 1222 the pattern to theknown pattern for a refrigerant leak, which is likely to show adegradation over a period of a few hours to a few days. If the patternof degradation matches the refrigerant leak paradigm, the server createsand transmits to the homeowner a message 1224 alerting the homeowner tothe possible problem. If the problem does not match the refrigerant leakparadigm, the system compares 1226 the pattern to the known pattern foran open window or door, which is likely to show significant changes forrelatively short periods at intervals uncorrelated with climaticpatterns. If the pattern of degradation matches the open door/windowparadigm, the server creates and transmits to the homeowner a message1228 alerting the homeowner to the possible problem. If the problem doesnot match the refrigerant leak paradigm, the system continues to stepthrough remaining know patterns N 1230 until either a pattern is matched1232 or the list has been exhausted without a match 1234.

FIG. 13 illustrates the steps involved in diagnosing inaccuratethermostat readings due to improper location. In step 1302, the serverretrieves climate data related to home X. Such data may include currentoutside temperature, outside temperature during the preceding hours,outside humidity, wind direction and speed, whether the sun is obscuredby clouds, and other factors. In step 1304, the server retrieves HVACduty cycle data for home X. Such data may include target settings set bythe thermostat in current and previous periods, the timing of switch-onand switch-off events and other data. In step 1306, the server retrievesdata regarding current and recent temperature readings as recorded bythe thermostat in home X. In step 1308, the server retrieves profiledata for home X. Such data may include square footage and number offloors, when the house was built and/or renovated, the extent to whichit is insulated, its address, make, model and age of its furnace and airconditioning hardware, and other data. In step 1310, the serverretrieves comparative data from other houses that have thermostats thatalso report to the server. Such data may include interior temperaturereadings, outside temperature for those specific locations, duty cycledata for the HVAC systems at those locations, profile data for thestructures and HVAC systems in those houses and the calculated thermalmass index for those other houses. In step 1312, the server calculatesthe expected thermostat temperature reading based upon the input data.In step 1314, the server compares the predicted and actual values. Ifthe calculated and actual values are at least roughly equivalent, theserver concludes 1316 that there is no thermostat-related anomaly. Ifthe calculated and actual values are not roughly equivalent, the serverretrieves additional historical information about past thermostatreadings in step 1318. In step 1320, the server retrieves solarprogression data, i.e., information regarding the times at which the sunrises and sets on the days being evaluated at the location of the housebeing evaluated, and the angle of the sun at that latitude, etc. In step1322, the server compares the characteristics of the anomalies overtime, to see if, for example, abnormally high readings began at 3:06 onJune 5^(th), 3:09 on June 6^(th), 3:12 on June 7^(th), and the solarprogression data suggests that at the house being analyzed, that sunwould be likely to reach a given place in that house three minutes lateron each of those days. If the thermostat readings do not correlate withthe solar progression data, the server concludes 1324 that the sun isnot causing the distortion by directly hitting the thermostat. If thethermostat readings do correlate with solar progression, the server thencalculates 1326 the predicted duration of the distortion caused by thesun. In step 1328, the server calculates the appropriate setpointinformation to be used by the thermostat to maintain the desiredtemperature and correct for the distortion for the expected length ofthe event. For example, if the uncorrected setpoint during the predictedevent is 72 degrees, and the sun is expected to elevate the temperaturereading by eight degrees, the server will instruct the thermostat tomaintain a setpoint of 80 degrees. In step 1330, the server sends thehomeowner a message describing the problem.

The system installed in a subscriber's home may optionally includeadditional temperature sensors at different locations within thebuilding. These additional sensors may be connected to the rest of thesystem via a wireless system such as 802.11 or 802.15.4, or may beconnected via wires. Additional temperature and/or humidity sensors mayallow increased accuracy of the system, which can in turn increase usercomfort or energy savings.

While particular embodiments have been shown and described, it isapparent that changes and modifications may be made without departingfrom the invention in its broader aspects and, therefore, the inventionmay carried out in other ways without departing from the true spirit andscope. These and other equivalents are intended to be covered by thefollowing claims:

What is claimed is:
 1. A system for controlling an HVAC system at auser's building, the system comprising: a memory; and one or moreprocessors; the one or more processors configured to receive a firstdata from at least one sensor, wherein the first data from the at leastone sensor includes a measurement of at least one characteristic of theuser's building; the one or more processors further configured toreceive a second data from a network connection, wherein the second datafrom the network connection is collected from a source external to thebuilding; the one or more processors further configured to receive afirst temperature setpoint for the building, wherein the first setpointincludes a temperature value and a time value; the one or moreprocessors further configured to predict, based at least on the firstdata from the sensor, the second data from the network connection, andthe first temperature setpoint, the time necessary for the HVAC systemto operate in order to reach the temperature value by the time value;and the one or more processors further configured to control the HVACsystem to operate to cause the building to reach the temperature valueby the time value.
 2. The system of claim 1, wherein the first data fromthe at least one sensor comprises a measurement of the currenttemperature and humidity of the building by the sensor.
 3. The system ofclaim 2, wherein the second data from the network connection comprises ameasurement of the current outdoor temperature.
 4. The system of claim3, wherein the second data from the network connection comprises ameasurement of the current outdoor humidity.
 5. The system of claim 3,wherein the one or more processors is further configured to receive atleast one setting of the HVAC system.
 6. The system of claim 5, whereinthe at least one setting of the HVAC system comprises whether the HVACsystem is currently on or off.
 7. The system of claim 5, wherein the atleast one setting of the HVAC system comprises whether the HVAC systemis operating in a cooling mode or a heating mode.
 8. The system of claim7, wherein the at least one setting of the HVAC system further comprisesthe length of time for which a stage of the HVAC system is scheduled tooperate.
 9. The system of claim 3, wherein the first data from the atleast one sensor comprises a measurement of ambient light level.
 10. Thesystem of claim 3, wherein the network connection is based on the IEEE802.11 wireless protocol.
 11. The system of claim 1, wherein the one ormore processors' prediction of the time necessary for the HVAC system tooperate in order to reach the temperature value by the time value isfurther based on calculating a rate of change value necessary for thebuilding to reach the temperature value by the time value.
 12. Thesystem of claim 11, wherein the one or more processors is furtherconfigured to control the HVAC system to operate to cause the buildingto reach the temperature value by the time value by adjusting a secondtemperature setpoint for the building based at least on the rate ofchange value.
 13. The system of claim 1, wherein the one or moreprocessors is further configured to receive a third data generated basedon a previous operation of the HVAC system, wherein the third dataincludes at least one performance characteristic of the HVAC system. 14.The system of claim 13, wherein the one or more processors' predictionof the time necessary for the HVAC system to operate in order to reachthe temperature value by the time value is further based on the thirddata.
 15. The system of claim 14, wherein the memory is furtherconfigured to store a fourth data comprising previously received indoortemperature data and outdoor temperature data, wherein the one or moreprocessors' prediction of the time necessary for the HVAC system tooperate in order to reach the temperature value by the time value isfurther based on the fourth data.
 16. The system of claim 1, wherein thememory is further configured to store historical values of the firstdata and second data.
 17. The system of claim 16, wherein the one ormore processors' prediction of the time necessary for the HVAC system atthe user's building to operate in order to reach the temperature valueby the time value is further based on analyzing the stored historicalvalues of the first data and second data.
 18. The system of claim 17,wherein the one or more processors is further configured to calculate aperformance characteristic of the HVAC system based at least on thehistorical values of the first data and second data.
 19. The system ofclaim 18, wherein the one or more processors' prediction of the timenecessary for the HVAC system at the user's building to operate in orderto reach the temperature value by the time value is further based onanalyzing the performance characteristic of the HVAC system.
 20. Thesystem of claim 1, wherein the one or more processors comprises a firstprocessor that is located remotely from the memory and not in electricalcontact with the memory.
 21. The system of claim 20, wherein theprediction of the time necessary for the HVAC system at the user'sbuilding to operate in order to reach the temperature value by the timevalue is performed by the first processor that is located remotely fromthe memory.
 22. The system of claim 21, wherein the controlling of theHVAC system to operate to cause the building to reach the temperaturevalue by the time value is performed by the first processor that islocated remotely from the memory.
 23. The system of claim 22, whereinthe first data from the at least one sensor is provided by a sensor thatis not electrically connected to the first processor that is locatedremotely from the memory.
 24. A system for controlling an HVAC system ata user's building, the system comprising: a memory; and a processor; theprocessor configured to receive a first data from a first sensor device;the processor configured to receive a second data from a second sensordevice located external to the system; the processor configured toreceive a first setpoint of the user, wherein the first setpointincludes a temperature value and a time value; the memory configured tostore the first data, second data, and first setpoint; the processorconfigured to predict, based at least on analyzing the first data, thesecond data, and the first setpoint, the time necessary for a HVACsystem at the user's building to operate in order to reach thetemperature value by the time value; the processor configured to controlthe HVAC system to operate to cause the building to reach thetemperature value by the time value; the processor configured to sendoperational instructions effective to control the HVAC system at theuser's building to operate to cause the building to reach thetemperature value by the time value.
 25. The system of claim 24, whereinthe processor's prediction of the time necessary for the HVAC system tooperate in order to reach the temperature value by the time value isfurther based on calculating a rate of change value necessary for thebuilding to reach the temperature value by the time value.
 26. Thesystem of claim 24, wherein the first data from the first sensorcomprises a measurement of indoor temperature at the user's building andthe second data from the second sensor device comprises a measurement ofoutdoor temperature.
 27. The system of claim 24, wherein the memory isfurther configured to store historical values of the first data andsecond data.
 28. The system of claim 27, wherein the processor'sprediction of the time necessary for the HVAC system at the user'sbuilding to operate in order to reach the temperature value by the timevalue is further based on analyzing the stored historical values of thefirst data and second data.
 29. The system of claim 27, wherein theprocessor is further configured to calculate a performancecharacteristic of the HVAC system based at least on the historicalvalues of the first data and second data.
 30. The system of claim 29,wherein the processor's prediction of the time necessary for the HVACsystem at the user's building to operate in order to reach thetemperature value by the time value is further based on analyzing theperformance characteristic of the HVAC system.